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Application Programming Interface Design and Scalability Questions

Designing application programming interfaces that remain reliable, performant, and maintainable at high scale. Candidates should understand how interface decisions affect scalability, availability, latency, and operational complexity and be able to reason about trade offs between client complexity and server responsibility. Core areas include stateless interface design, pagination and cursor strategies for large result sets, filtering and search optimization, payload minimization, batching and streaming, and techniques to reduce server load while preserving client experience. Resilience and operational controls include rate limiting and quota management, throttling, backpressure and flow control, retry semantics and idempotency patterns, error format design and explicit identification of retryable errors, and strategies for graceful degradation under overload. Evolution and compatibility topics include backward compatible versioning strategies, deprecation policies, contract design and testing approaches to avoid breaking consumers. Infrastructure and deployment considerations include API gateway and edge patterns, interaction with load balancers and traffic distribution, caching and content delivery, routing fault tolerance, health checks and canary rollout strategies, and observability through metrics, distributed tracing, and logging to support capacity planning and incident response. Security considerations such as scalable authentication and authorization, credential and key management, and permission models are also important. Candidates should be prepared to discuss concrete patterns, trade offs, algorithms, and operational playbooks for designing and running high traffic application programming interfaces.

HardTechnical
0 practiced
Design a coordinated retry policy across a chain of dependent services to avoid retry storms and cascading failures. Include client-side backoff policies, service-level circuit breakers and bulkheads, server-provided Retry-After semantics, centralized orchestration vs decentralized rules, and approaches for asynchronous retries with dead-letter handling.
MediumTechnical
0 practiced
As a solutions architect, list the key metrics, traces, and logs you would instrument for a public API to support capacity planning and incident response. Include dimensionality examples (by endpoint, tenant, region), latency percentiles, error budgets, sampled distributed traces, and log correlation keys. Explain a tagging strategy and trade-offs with metric cardinality.
HardSystem Design
0 practiced
Design an edge-caching strategy for a CDN in front of APIs that serve mutable resources like user profiles. Address cache key design, TTLs, invalidation strategies (purges vs surrogate keys), signed URLs, private vs public caching, and how to maintain data correctness while maximizing cache hit ratio and reducing origin load.
HardTechnical
0 practiced
Explain how to implement backpressure propagation end-to-end in a microservices mesh, from clients through API gateway to downstream services. Cover transport-level flow control (HTTP/2, gRPC), application-level signals, queue depth limits, circuit breakers, token bucket throttling, and how to surface explicit backpressure information to clients.
MediumTechnical
0 practiced
List techniques to minimize payload size for mobile API clients, including field projections, compression, binary encodings, delta sync, pagination, and server-driven content negotiation. For each technique describe server and client implications, CPU and bandwidth tradeoffs, and compatibility concerns when evolving schemas.

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